I thought this would be a good photo to start the post on EuroQSAR 2010. It really was great fun to be in Rhodes and to catch up with a lot of folk whom I've not seen for a while. The photo was taken at Delphi the day after the conference ended. This the Temple of Apollo where the priestess in residence would inhale hot gases and make predictions... of course nothing like QSAR!
You may well ask what a conference on QSAR has to do with FBDD so I'll try to make the connection clearer. The central problem in QSAR is prediction of affinity so it's a good idea to maintain awareness of the field if you're planning to exploit protein or ligand structures in selection of fragments for screening. Also if you're planning to analyse and design compound libraries or assess druggability then it's useful to know a bit about the molecular descriptors and data analytic methods that form the basis of modern QSAR.
The ultimate goal in QSAR is to start with a molecular structure and predict the physiological effects of the compound. In order to to this you need to be able to predict the extent to which the drug binds to its primary target and a number of anti-targets. You can calculate the extent of binding from the affinity of the drug and its unbound (e.g. to plasma protein) concentration in the vicinity of the target. With typical dosing the unbound drug concentration is a function of both time and location (e.g. intracellular versus extracellular) within the body. If that sounds unbearably complex then I should warn you that it can get a whole lot worse because binding might be slow and you might also need to worry about things like reactive metabolites, isoforms and how toasted the patient got in the pub the night before.
I believe that we're a very long way off seeing this goal achieved. Even when the structure of a protein is known, prediction of affinity for an arbitrary ligand is just not accurate enough. Prediction of unbound concentration at arbitrary location in the body is equally difficult although for some targets it may be sufficient to know the unbound plasma concentration. Nevertheless it is possible to build useful models for some of the pieces in this jigsaw (e.g. binding to plasma protein; IC50 for series of chemically similar receptor antagonists) especially when the process in question is strongly influenced by lipophilicity. QSAR models can be local (i.e. only applicable within a restricted regions of chemical space such as a series of analogs) or global (applicable to any arbitrary molecule). My view is that QSAR models presented as global are frequently ensembles of local models and I have expressed this opinion in print.
I guess that something should be said about the talks after such a long-winded introduction. Some of the speakers have made their lecture slides available. I should first point out that I managed to miss the only talk specifically on FBDD because I was retrieving my camera from my hotel room so that I could photograph a friend doing her poster presentation. The inaugural lecture is given by Hugo Kubinyi and although I saw 'The long road from QSAR to virtual screening' two and a half years ago at an OpenEye meeting in Strasbourg, it is still amusing to see polar surface area and connectivity descriptors cop some flak.
Anthony Nicholls delivers a stimulating lecture entitled 'Information Theory & QSAR'. Nearest neighbor models crop up in more than once in this talk and I liked the suggestion that in validation we should be 'making tests NN resistant'. Nearest neighbours also make an appearance in Han van de Waterbeemd's talk (Assessing Drug Safety and Efficacy through ADME predictions) in the context of 'correction libraries'. The idea behind a correction library is to see if there are systematic errors in the predicted values of a property for near neighbours of the compound for which you're making a prediction. If so the differences between the values measured for the neighbor and predicted for them by the model can be used to correct predictions for new compounds. Of course Orwell would have said that all QSAR models are global...
I enjoyed (not least because he did not appear over-awed by the illustrious inaugural lecturer) the lecture by Alex Tropsha entitled 'Novel Approaches to Chemical Toxicity Prediction Relying on the Entire Structure- in vitro in vivo Data Continuum'. Attempting to sum up the talk in one sentence, I'd say that this was a view of how QSAR modelling might be used to integrate diverse data types that vary in complexity and noise level. One comment that I captured from the 'Notes on chemical descriptors' slide (#14; it's marked 'de-Ku' at bottom left) was that 'descriptors are designed to reflect uniqueness of a molecule in comparison with other molecules'. What does this say about nearest neighbours, I wonder...
Jordi Mestres makes the point in his talk, entitled 'Ligand-based Approaches to In-Silico Pharmacology', that we should STOP using the word 'polypharmacology'. I couldn't agree more although I think the term 'pharmacodynamics' is a couple of orders of magnitude more meaningless. This lecture is about predicting affinity across a range of GPCRs and how these affinity profiles might be used, for example, to anticipate side effects of drugs. Intracellular targets will add complexity because less will be known about unbound concentration of drug in the vicinity of the target.
There's also a session on design of agrochemicals kicked off by Klaus-Juergen Schleifer. All molecular design is subject to constraints and it is always educational to see how people designing molecules for different purposes deal with the constraints that apply to them. Designers of agrochemicals need to deal with different species of plants, fungi and insects in a chemical-unfriendly (e.g. bright sunlight, rain) environment. Pharmaceutical QSAR modellers may find that they learn more in an agrochemical session than a pharmaceutical one.
I must confess to being less than alert on the Friday morning and this may have something to do with over-indulging at the conference dinner and ending up on the beach at 2AM (it seemed a good idea at the time but then it always does). Eric Martin describes how QSAR methodology can be used to integrate affinity and protein structural data for protein kinase inhibitors. Tudor Oprea's lecture (Computer-Aided Drug Re-purposing) is notable because of the use of experimental pharmacokinetic data (this is typically available for marketed drugs) to get a handle on unbound plasma concentration. Aspiring systems biologists, take note.
I've taken a look at some of the talks and it's a good time to summarise before getting on to the fun bit where I share some pictures. Firstly I do not see prediction of affinity for arbitrary molecules (e.g. when there is no measured data for analogs) something we can currently do in a useful and general manner. Secondly, I don't see model validation as a solved problem and a session on the subject is something that the Scientific Committee may wish to think about for EuroQSAR2012 in Vienna. Thirdly remember that, "A theory has only the alternative of being right or wrong. A model has a third possibility: it may be right, but irrelevant" (Manfred Eigen).
The excursion to Lindos provides an excellent opportunity get some pictures. First to be papped is fellow AZ-escapee Han.
I sneak up on Anna (who also doesn't work at AZ any more) as we wait for the bus.
Dick is the man behind CoMFA and Topomers and I've lost count of the number of conferences which we have both attended.
Unfortunately I can't get Yvonne to look at the camera. To her right is Cynthia who co-chaired the session on descriptors in which Yvonne and I both did talks. Andreas and Ylva are smiling because I've told them that the chef has got rotted herring on the menu for the conference dinner.
I finally catch Yvonne as we're waiting for the bus back. I'd not seen Eric since the mid-90s so it's good to get the two of them together in this photo.
David (make sure you're in a country with an almost worthless unit of currency should you presume in his presence otherwise prepare to pay out big time) and Frank have been in this business a long time.
Portraits from the conference dinner.
David is animated but Ant looks in need of a dose of the Poisson-Boltzmanns.
Dimitris appears strangely unconcerned to be in the company of two Transylvanians who are discussing anticoagulant QSVRs (Quantitative Structure Viscosity Relationships) as they admire the tone of his carotid arteries.
Graduate students. Birte (4th from left) did a talk and both Juliana (2nd from left) and Andrea (3rd from left) had their posters selected for oral presentation.